Data was not normally distributed so Spearman’s correlation was used to look at the relationship between CO2 emissions and GDP per capita in 1962. The correlation coefficient was 0.85 with a p-value of 0.
Data was not normally distributed so a Spearman’s correlation was used. Correlation between CO2 emissions and GDP per capita was highest in 2002.
Before comparing energy use in different continents, a quantile-quantile plot was used to check the normality of energy use data.
Because the data was not normally distributed, a Kruskal-Wallis test and Wilcoxon test was used was used to compare the average energy use in different continents since 1962.
There were significant differences in energy use between continents, with Oceania having the highest consumption per capita.
A quantile-quantile plot was used to check the normality of imports data in Europe and Asia after 1990.
A Shapiro-Wilk test was also used. The p-value was 1.46e-13 which is less than 0.05 which means that the data is not normally distributed. Therefore, a Wilcoxon rank-sum test was used compare imports between Europe and Asia.
There was no significant difference between Europe and Asia (p>0.05) with respect to the percentage of GDP that accounts for imports of goods and services in any years since 1990.
This table shows the top 5 countries with the highest average ranking in population density across all time points.
The two countries with the highest average ranking in population density were Macao SAR, China and Monaco.
The table below shows countries with the greatest incresease in life expectancy since 1962.
The country with the greatest increase in life expectancy since 1962 was Maldives with an increase of 36.92 years.